The present invention generally relates to medication management. More specifically, the present invention relates to systems and methods for advanced order medication management.
Healthcare environments, such as hospitals or clinics, include information systems, such as hospital information systems (HIS), radiology information systems (RIS), clinical information systems (CIS), and cardiovascular information systems (CVIS), and storage systems, such as picture archiving and communication systems (PACS), library information systems (LIS), and electronic medical records (EMR). Information stored may include patient medical histories, imaging data, test results, diagnosis information, management information, and/or scheduling information, for example. The information may be centrally stored or divided at a plurality of locations. Healthcare practitioners may desire to access patient information or other information at various points in a healthcare workflow. For example, during surgery, medical personnel may access patient information, such as images of a patient's anatomy, that are stored in a medical information system. As another example, medical personnel may enter new orders for patients. Orders may include, for example, basic medication to be given to a patient and/or a procedure or exam to be conducted.
Orders may be entered or written using an order entry system such as a Computerized Provider Order Entry (CPOE) application, for example. Orders may include, for example, basic medications, lab tests, and/or procedures. For example, a user may specify 500 mg of aspirin to be administered to the patient with the order entry system. As another example, a user may write an order to schedule a procedure for a patient using CPOE. Current systems allow only simple orders such as, for example, 500 mg of aspirin to be given every 6 hours. As another example, the order entry system may be capable of allowing a user to review, change, and/or cancel existing orders; configure default rules for specifying an order; and/or provide interaction checking for medications ordered. Interaction checking may include, for example, drug-to-drug interactions, dose range warnings, drug allergies, duplicate drugs, and/or therapeutic duplication.
A Medication Administration Record (MAR) application is a tool for health care providers such as nurses. The MAR application allows a health care provider to see, monitor, and chart the administration of medication. For example, 500 mg of aspirin may be prescribed, but only 250 mg may actually have been given because the patient was not feeling as bad at the time the dosage was given. The MAR application may indicate what medication has been prescribed and when it should be administered. In addition, the MAR application may allow a user to update the status of an order, for example, the user may indicate what was actually administered.
A Pharmacy (Rx) application is utilized by a health care provider such as a pharmacist. The Rx application handles charging and dispensing medications. In addition, the Rx application may allow a user to view existing medications that have been prescribed. In current systems, a pharmacist may manually examine and/or approve an order. The pharmacist may have to manually re-enter and/or process an order with the Rx application based on comments or notations for the order.
Clinical decision support systems provide assistance to healthcare providers such as physicians. For example, clinical decision support systems can aid a physician in making decisions regarding diagnosis and/or treatment. As another example, clinical decision support systems may perform interaction checking on prescription orders for possible adverse drug interactions. A clinical decision support system may be part of a CIS and/or HIS, for example. A clinical decision support system may utilize information stored in and/or received from other systems such as RIS, CVIS, PACS, LIS, EMR, CPOE, and/or Rx, for example. Clinical decision support systems may process, for example, orders from a CPOE application and/or lab results using rules or other criteria to provide recommendations to a health care provider.
Current systems may utilize a standard protocol to link one or more systems such as CPOE, MAR, and/or Rx applications. An example of one such protocol is HL7. HL7 provides for some kinds of structured communication of coded health care information between computer applications. Standard protocols such as HL7 may provide unused and/or comment fields or segments to convey information not supported by the protocol. However, such information, since it is not part of the standard, must be manually and/or individually processed.
Current systems linking applications such as CPOE applications, MAR applications, and Rx applications, using, for example, HL7, do not provide integrated support for advanced types of orders. That is, current systems support at most simple orders that include only dosage, start day, stop day, and frequency. In contrast, an advanced order may include orders with complex combinations of additives, parts, and/or scheduling. For example, advanced orders may include sliding scales, total parenteral nutrition (TPN), fluids with additives, taper orders, and/or linked sub-orders. For example, a TPN order may include 500 mg of potassium with vitamins and amino acids, 20-percent lipids, and 10-percent fluid. As another example, an advanced order could include scheduling such as 3 mg every Monday, Wednesday, Friday, and 5 mg every Tuesday, Thursday. Advanced orders may include linked and/or related sub-orders and/or additives. For example, a taper order for Prednisone, from which a patient must be weaned, may include linked and/or related sub-orders providing for 100 mg for the first two days, and then subsequent day 10 mg less than the last dosage. As another example, a fluids with additives advanced order may include the related additives in the order for the fluids.
Current systems, to support any form of advanced order at all, require each component to be individually entered, with no relation or link between them, and/or unstructured comments to be placed in orders that must be manually read and interpreted by an end user. Such unstructured comments are un-coded and thus unusable for automatic procedures such as interaction checking or for use by the Rx system for processing and/or fulfillment. Thus, pharmacists must build the order again in their system after manually interpreting the comments.
Thus, there is a need for a system and method for advanced order medication management.